Decision making in a commercial breeding program - BrIN Learning Series

Date: 
May 6, 2021

For: Plant breeders, quantitative geneticists, breeding analytics developers, biometricians, bioinformaticians, and the BrIN community

By: Bayer, EiB, Cornell University, IITA, CIMMYT, IRRI

Watch the webinar: (recorded May 6, 2021)

 

Download the presentation PDF: Click here

Questions for the presenter: can be submitted here

Event description:

Decision making in a commercial breeding program - Breeding Informatics Network Community Learning Series 

An expert presentation and discussion on how Bayer increased data fluency and analytics to make better decisions. What did they learn and what changes were adopted over the last 10 years? Join Bayer, Cornell, EiB and partners for an examination of how over the years of testing, Bayer has aimed to get increasing confidence for performance in farmers’ fields and conditions. This includes increasing the number of locations and size of experimental plots.

Brian Gardunia of Bayer Crop Science describes data analytics used for decision making and how that helps ensure confidence that the right varieties and hybrids have been selected to sell. The presentation is followed by Q&A.

Webinar objectives: The webinar will help participants understand:

  • What data-driven modern breeding programs look like
  • How data analytics are routinely used in modern breeding programs
  • How data analytics can shorten the breeding cycle, improve operation efficiencies, and selection accuracies, and genetic gains

Presenter: Brian Gardunia, Bayer Crop Science

Hosts: Breeding Informatics Network (BrIN) Lead/Project Manager, Young Wha Lee, EiB / Star Gao, Cornell University

 

Special thanks: to EiB project funders including Bill & Melinda Gates Foundation, the UK Foreign, Commonwealth & Development Office, the United States Agency for International Development, GIZ/BMZ Germany, ACIAR Australia, the Foundation for Food and Agricultural Research (FFAR), and our presenters and partners.

 

Short description: 
An expert presentation and discussion on how Bayer increased data fluency and analytics to make better decisions. What did they learn and what changes were adopted over the last 10 years? Join Bayer, Cornell, EiB and partners for an examination of how over the years of testing, Bayer has aimed to get increasing confidence for performance in farmers’ fields and conditions.